Job Details

Job Location: Chennai (Guindy) WeWork Office (5 Days Work from Office)
Exp: 5 to 12 Years

We are seeking a Senior AI Engineer with deep expertise in Reinforcement Learning (RL) and
Neural Networks to lead the evolution of our AI core for gaming applications, specifically in
imperfect information games like poker. This role offers the opportunity to work on ground
breaking innovations, collaborate with industry leaders, and gain visibility as a domain expert
through publications and conferences.

Key Responsibilities:
Lead the development and evolution of our AI core, currently built in C++, towards the
next generation of algorithms and architectures.
The main responsibility is to lead the evolution of our AI core to the next level.
Included the opportunity to get visibility as an industry expert through the publishing of
papers, conferences, and so on, to make it more appealing.
Design, implement, and optimize advanced RL algorithms tailored for imperfect
information games.
Research and integrate state-of-the-art techniques in RL, neural networks, and game
theory to enhance AI performance and scalability.
Collaborate with cross-functional teams to identify challenges and innovate AI-driven
solutions.
Evaluate and fine-tune AI models for decision-making, strategy optimization, and real-
time applications in gaming.
Profile, optimize, and troubleshoot the AI core for high-performance execution across
different computing architectures (e.g., CPU, GPU, or custom accelerators).
Document methodologies, experiments, and results to ensure transparency and
reproducibility.

Required Skills and Qualifications:
Bachelors, Master’s, or Ph.D. in Computer Science, Mathematics, Physics, Artificial
Intelligence, or a related field.
3+ years of experience in AI/ML, with a strong focus on Reinforcement Learning and
Neural Networks.
Proficiency in programming languages commonly used in AI, such as C++, Python,
Julia, or others relevant to your expertise.
In-depth understanding of game theory, especially concepts like Nash equilibrium and
strategies in imperfect information games.
Expertise in RL frameworks and tools like OpenSpiel, RLlib, or similar libraries tailored
for game AI.
Strong knowledge of RL algorithms, and experience with neural network architectures.
Familiarity with parallel computing, performance profiling, and optimization techniques.
Excellent problem-solving skills, with the ability to work independently and in a team.

Preferred Skills:
Experience with multi-agent RL or hierarchical RL in gaming contexts.
Background in poker AI or similar imperfect information games.
Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Knowledge of distributed systems, parallel programs, or cloud-based AI deployments.
Published research or contributions to open-source AI projects in RL or game AI.
What We Offer:

The opportunity to work on cutting-edge AI applications in gaming and lead innovations
in imperfect information games.
Support for publishing research papers, presenting at conferences, and gaining visibility
as a world domain expert in the field.
A collaborative and intellectually stimulating work environment with a team passionate
about pushing the boundaries of AI.
Flexibility and resources to experiment with state-of-the-art techniques and contribute to
open-source projects.

Soft Skills:
Effective communication for collaborating with cross-functional teams and presenting
complex ideas clearly.
Passion for innovation and driving the next generation of AI in gaming.